Environment Mapping and Other Applications of World Projections

Accurate precise positioning at millimeter wave frequencies is possible due to the large available bandwidth that permits precise on-the-fly time of flight measurements using conventional air interface standards. In addition, narrow antenna beamwidths may be used to determine the angles of arrival and departure of the multipath components between the base station and mobile users. By combining accurate temporal and angular information of multipath components with a 3-D map of the environment (that may be built by each user or downloaded a-priori), robust localization is possible, even in non-line-of-sight environments. In this work, we develop an accurate 3-D ray tracer for an indoor office environment and demonstrate how the fusion of angle of departure and time of flight information in concert with a 3-D map of a typical large office environment provides a mean accuracy of 12.6 cm in line-of- sight and 16.3 cm in non-line-of-sight, over 100 receiver distances ranging from 1.5 m to 24.5 m using a single base station. We show how increasing the number of base stations improves the average non-line-of-sight position location accuracy to 5.5 cm at 21 locations with a maximum propagation distance of 24.5 m.

Environment maps, like texture maps or any other maps consisting of discretely stored data have to be properly filtered, if they are being resampled in the process of rendering an image. For environment maps, this is especially important, as the sampling rate is subject to extreme changes due to the curvature of the reflecting surfaces. However, for the same reason, the antialiasing is especially difficult to perform, as the sampling rate has to be determined for each pixel. We introduce a method to perform this calculation and determine the parameters for anisotropic filtering of the environment map. Instead of the BRDF, we employ roughness pyramids to account for the properties of the reflecting surface. The principles that are used to perform this antialiasing can be applied for antialiasing reflected textures in general e.g. in ray tracing.

Photo-realistic rendering algorithms such as Monte Carlo ray tracing sample individual paths to compute images. Noise and aliasing artefacts are usually reduced by supersampling. Knowledge about the neighborhood of the path, such as an estimated footprint, can be used to reduce these artefacts without having to trace additional paths. The recently introduced ray differentials estimate such a footprint for classical ray tracing, by computing ray derivatives with respect to the image plane. The footprint proves to be useful for filtering textures locally on surfaces. In this paper, we generalize the use of these derivatives to arbitrary path sampling, including general reflection and refraction functions. Sampling new directions introduces additional partial derivatives, which are all combined into a footprint estimate. Additionally the path gradient is introduced; it gives the rate of change of the path contribution. When this change is too steep the size of the footprint is reduced. The resulting footprint can be used in any global illumination algorithm that is based on path sampling. Two applications show its potential: texture filtering in distributed ray tracing and a novel hierarchical approach to particle tracing radiosity.

Increasingly, scholars, policy makers, and others have put forth that governance and management of urban environments requires a consideration of cities as social-ecological systems, necessitating involvement from a broad range of actors. Yet the research on environmental governance and development of tools to support it is often completed for rather than with those responsible for carrying out the work. We examined a university-led research effort on urban environmental stewardship in Los Angeles (LA), USA. A university urban research center conducted an environmental Stewardship Mapping and Assessment Project (STEW-MAP) in Los Angeles County, which draws upon network analysis and GIS to better understand sustainability relationships, opportunities, and gaps. STEW-MAP is intended to be both a research study examining stewardship organizations across sectors, scales, jurisdictions and geographic space, as well as an application providing tools to facilitate collaborative environmental stewardship. We sought to contribute to a better understanding of how the process of STEW-MAP can leverage sustainability for a more relational ecology with cities approach. To evaluate the process of the LA STEW-MAP, we conducted our conceptual analysis of this stewardship tool by examining co-production of knowledge and co-production of place, drawing particularly from workshops with community partners that took place in 2017 and 2018. This article will show that the LA STEW-MAP process can be improved to better operationalize a relational ecology with cities approach. This research contributes to the urban sustainability governance literature by focusing on how the process of the LA STEW-MAP can be a relational model and advance an ecology with cities' approach that captures and leverages multi-scalar interactions.

A review of the last 50 years finds that the traditional breakdown of Soviet cartography into its specialized research disciplines no longer conforms to current needs. Soviet cartography has been divided historically into mathematical cartography, map science (the study of maps and their uses), map compilation and editing, map design and production. A growing specialization in cartography by thematic disciplines (geomorphic mapping, agricultural mapping, etc.) with widely differing requirements and principles of compilation and editing suggests the need for a restructuring of the research disciplines. In addition to mathematical cartography, concerned with map projections and map measurements, the new structure would include: technical cartography (the study of source materials, map design and production); natural-historic cartography (principles of compilation and editing of maps of the physical environment), and socioeconomic cartography (concerned with the mapping of human phenomena).

Video object segmentation for automatic image annotation of ethernet connectors with environment mapping and 3D projection

Visual coherence between real and virtual objects is important in mixed reality (MR), and illumination consistency is one of the key aspects to achieve coherence. Apart from matching the illumination of the virtual objects with the real environments, the change of illumination on the real scenes produced by the inserted virtual objects should also be considered but is difficult to compute in real-time due to the heavy computation demands of global illumination. In this work, we propose delta path tracing (DPT), which only computes the radiance blocked by the virtual objects from the light sources at the primary hit points of Monte Carlo path tracing, then combines the blocked radiance and multi-bounce indirect illumination with the image of the real scene. Multiple importance sampling (MIS) between BRDF and environment map is performed to handle all-frequency environment maps captured by a panorama camera. Compared to conventional differential rendering methods, our method can remarkably reduce the number of times required to access the environment map and avoid rendering scenes twice. Therefore, the performance can be significantly improved. We implement our method using hardware-accelerated ray tracing on modern GPUs, and the results demonstrate that our method can render global illumination at real-time frame rates and produce plausible visual coherence between real and virtual objects in MR environments.

Ray tracing theory is still important in order to understand algorithms like Whitted ray tracing or path tracing when it comes to global illumination. An important role is played by the theory behind the lighting and shading of surfaces, and the rendering equation is central when it comes to light transport and shading. In this chapter, you will learn how the propagation of light is fully described by the aforementioned equation.

Effect of collector components on the collection efficiency of tubular evacuated collectors with diffuse reflectors

A molecular map has been constructed for the rice genome comprised of 726 markers (mainly restriction fragment length polymorphisms; RFLPs). The mapping population was derived from a backcross between cultivated rice, Oryza sativa, and its wild African relative, Oryza longistaminata. The very high level of polymorphism between these species, combined with the use of polymerase chain reaction-amplified cDNA libraries, contributed to mapping efficiency. A subset of the probes used in this study was previously used to construct an RFLP map derived from an inter subspecific cross, providing a basis for comparison of the two maps and of the relative mapping efficiencies in the two crosses. In addition to the previously described PstI genomic rice library, three cDNA libraries from rice (Oryza), oat (Avena) and barley (Hordeum) were used in this mapping project. Levels of polymorphism detected by each and the frequency of identifying heterologous sequences for use in rice mapping are discussed. Though strong reproductive barriers isolate O. sativa from O. longistaminata, the percentage of markers showing distorted segregation in this backcross population was not significantly different than that observed in an intraspecific F2 population previously used for mapping. The map contains 1491 cM with an average interval size of 4.0 cM on the framework map, and 2.0 cM overall. A total of 238 markers from the previously described PstI genomic rice library, 250 markers from a cDNA library of rice (Oryza), 112 cDNA markers from oat (Avena), and 20 cDNA markers from a barley (Hordeum) library, two genomic clones from maize (Zea), 11 microsatellite markers, three telomere markers, eleven isozymes, 26 cloned genes, six RAPD, and 47 mutant phenotypes were used in this mapping project. Applications of a molecular map for plant improvement are discussed.

The application of projective mapping to quickly gather information on overall product differences provides a unique way to probe consumer perceptions and gather product information. A group of 15 consumers performed a projective mapping exercise three times on a set of eight “berry flavored” granola bars, including descriptors of the products. The projective mapping task was performed in replicates to evaluate the consistency of results obtained via this technique. Analysis of the replications by multifactor analysis indicated for the majority of consumers, that the three individual maps did not show a high degree of similarity (80% of RV coefficients < 0.5). However, consensus maps from the three replications indicated a similar group perception of the products over the replications, as depicted by hierarchical multifactor analysis. Terms collected from the maps were summarized and regressed into the product space for interpretation, both in terms of consumer criteria used to differentiate among products and identification of key product attributes. PRACTICAL APPLICATIONS The findings from this study add to the growing knowledge on projective mapping. The results presented here aimed to substantiate the value and reliability of projective mapping when used with consumers. Although projective mapping is not a replacement for quantitative descriptive analysis, it is an efficient tool for consumer research; as well as product or category exploration which can be utilized early in the product development process. The addition of descriptors directly onto the maps by panelists makes it possible to use projective mapping as a stand-alone method by increasing the amount and interpretability of data provided by panelists. When used with consumers, projective mapping links the consumer perception of the product space with a consumer-driven lexicon.

The ever increasing amount of data and processing capabilities – following the well- known Moore's law – is challenging the way scientists and engineers are currently exploiting large datasets. The scientific visualization tools, although quite powerful, are often too generic and provide abstract views of phenomena, thus preventing cross disciplines fertilization. On the other end, Geographic information Systems allow nice and visually appealing maps to be built but they often get very confused as more layers are added. Moreover, the introduction of time as a fourth analysis dimension to allow analysis of time dependent phenomena such as meteorological or climate models, is encouraging real-time data exploration techniques that allow spatial-temporal points of interests to be detected by integration of moving images by the human brain. Magellium is involved in high performance image processing chains for satellite image processing as well as scientific signal analysis and geographic information management since its creation (2003). We believe that recent work on big data, GPU and peer-to-peer collaborative processing can open a new breakthrough in data analysis and display that will serve many new applications in collaborative scientific computing, environment mapping and understanding. The magHD (for Magellium Hyper-Dimension) project aims at developing software solutions that will bring highly interactive tools for complex datasets analysis and exploration commodity hardware, targeting small to medium scale clusters with expansion capabilities to large cloud based clusters.

The Environmental Mapping and Analysis Program (EnMAP), is a new spaceborne German hyperspectral satellite mission for monitoring and characterizing the Earth&amp;#8217;s environment on a global scale. EnMAP mission supports the retrieval of high-quality and abundant detailed spectral information in VNIR and SWIR ranges within a large-scale area in wide temporal coverage and high spatial resolution. Taking advantage of high-quality data freely available to the scientific community great potential is revealed in a wide range of ecological and environmental applications, such as i.e. accurate and up-to-date LULC thematic maps.The objectives of the present study are to explore the accuracy of EnMAP in land cover mapping over a heterogeneous landscape. As a case study is used a typical Mediterranean setting located in Greece. The methodology is based on the synergistic use of machine learning techniques and ENMAP imagery coupled with other ancillary data and was carried out in EnMAP Box-3, a toolbox designed within a GIS open-source software. Validation of the derived LULC maps has been carried out using the standard error matrix approach and also via comparisons versus existing LULC operational products.To our knowledge, this research is one of the first to explore the advantages of the hyperspectral EnMAP satellite mission in the context of LULC mapping. Results of the present study are expected to provide valuable input for applications of LULC mapping and demonstrate the potential of hyperspectral EnMAP data for improved performance and the highest accuracy of LULC mapping.&amp;#160;KEYWORDS:&amp;#160;EnMAP,&amp;#160;Land cover, Land use, Hyperspectral remote sensing, Machine Learning

Autonomous mapping, especially in the form of SLAM (Simultaneous Localization And Mapping), has long since been used for many indoor robotic applications and is also useful in outdoor intelligent vehicle applications such as object detection. Most existing research works on environment mapping and object detection in outdoor applications have been dedicated to single vehicle system. On the other hand, multi-vehicle cooperative perception based on inter-vehicle data sharing can bring considerable benefits in many scenarios that are challenging for a single vehicle system. In this paper, a new method for occupancy grid maps merging is proposed: an objective function based on occupancy likelihood is introduced to measure the consistency degree of maps alignment; genetic algorithm implemented in a dynamic scheme is adopted to optimize the objective function. A scheme of multi-vehicle cooperative local mapping and moving object detection using the proposed occupancy grid maps merging method is also introduced. Real-data tests are given to demonstrate the effectiveness of the introduced method.

The radiation scattering in textured solar cell surfaces is usually analyzed by means of a ray optics approach. In this work, the authors investigate the validity of this technique for the particular case of a periodic grating of triangular profile. The problem is solved using a rigorous method from electromagnetism, the modal multilayer and the reflected radiation and its deviation from the ray optics approach is obtained. A perfect conducting medium is considered. The propagating modes show deviations from the ray optics approach, even for wavelength-period ratios (/spl lambda//d) of the order of 0.1. Since values of /spl lambda//d examined are of interest in photovoltaics, the authors conclude that EM effects must be taken into account in order to obtain accurate estimations of the radiation effectively absorbed in semiconductor textured surfaces.